Tail probabilities of the maxima of multilinear forms and their applications

被引:0
|
作者
Kuriki, S
Takemura, A
机构
[1] Inst Stat Math, Minato Ku, Tokyo 1068569, Japan
[2] Univ Tokyo, Fac Econ, Bunkyo Ku, Tokyo 1130033, Japan
来源
ANNALS OF STATISTICS | 2001年 / 29卷 / 02期
关键词
Gaussian field; Karhunen-Loeve expansion; largest eigenvalue; multiple comparisons; multivariate normality; multiway layout; PARAFAC; projection pursuit; tube formula; Wishart distribution;
D O I
暂无
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Let Z be a k-way array consisting of independent standard normal variables. For column vectors h(1), ..., h(k), define a multilinear form of deg-ree k by (h(1) circle times . . . circle times h(k))'vec(Z). We derive formulas for upper tail probabilities of the maximum of a multilinear form with respect to the h(i)'s under the condition that the h(i)'s are unit vectors, and of its standardized statistic obtained by dividing by the norm of Z. We also give formulas for the maximum of a symmetric multilinear form (h(1) circle times . . . circle times h(k))'vec(sym(Z)), where sym(Z) denotes the symmetrization of Z with respect to indices. These classes of statistics are used for testing hypotheses in the analysis of variance of multiway layout data and for testing multivariate normality. In order to derive the tail probabilities we employ a geometric approach developed by Hotelling, Weyl and Sun. Upper and lower bounds for the tail probabilities are given by reexamining Sun's results. Some numerical examples are given to illustrate the practical usefulness of the obtained formulas, including the upper and lower bounds.
引用
收藏
页码:328 / 371
页数:44
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